Potencialidad de la modelización state-space y el filtro de Kalman para el anàlisis regional : una aplicación para el índice de actividad industrial

El déficit existente a nuestro país con respecto a la disponibilidad de indicadores cuantitativos con los que llevar a término un análisis coyuntural de la actividad industrial regional ha abierto un debate centrado en el estudio de cuál es la metodología más adecuada para elaborar indicadores de estas características. Dentro de este marco, en este trabajo se presentan las principales conclusiones obtenidas en anteriores estudios (Clar, et. al., 1997a, 1997b y 1998) sobre la idoneidad de extender las metodologías que actualmente se están aplicando a las regiones españolas para elaborar indicadores de la actividad industrial mediante métodos indirectos. Estas conclusiones llevan a plantear una estrategia distinta a las que actualmente se vienen aplicando. En concreto, se propone (siguiendo a Israilevich y Kuttner, 1993) un modelo de variables latentes para estimar el indicador de la producción industrial regional. Este tipo de modelo puede especificarse en términos de un modelo statespace y estimarse mediante el filtro de Kalman. Para validar la metodología propuesta se estiman unos indicadores de acuerdo con ella para tres de las cuatro regiones españolas que disponen d¿un Índice de Producción Industrial (IPI) elaborado mediante el método directo (Andalucía, Asturias y el País Vasco) y se comparan con los IPIs publicados (oficiales). Los resultados obtenidos muestran el buen comportamiento de l¿estrategia propuesta, abriendo así una línea de trabajo con la que subsanar el déficit al que se hacía referencia anteriormente

Using the HEGY Procedure When Not All Roots Are Present

Empirical studies have shown little evidence to support the presence of all unit roots present in the $^{\Delta_4}$ filter in quarterly seasonal time series. This paper analyses the performance of the Hylleberg, Engle, Granger and Yoo (1990) (HEGY) procedure when the roots under the null are not all present. We exploit the Vector of Quarters representation and cointegration relationship between the quarters when factors $(1-L),(1+L),\bigg(1+L^2\bigg),\bigg(1-L^2\bigg) y \bigg(1+L+L^2+L^3\bigg)$ are a source of nonstationarity in a process in order to obtain the distribution of tests of the HEGY procedure when the underlying processes have a root at the zero, Nyquist frequency, two complex conjugates of frequency $^{\pi/2}$ and two combinations of the previous cases. We show both theoretically and through a Monte-Carlo analysis that the t-ratios $^{t_{{\hat\pi}_1}}$ and $^{t_{{\hat\pi}_2}}$ and the F-type tests used in the HEGY procedure have the same distribution as under the null of a seasonal random walk when the root(s) is/are present, although this is not the case for the t-ratio tests associated with unit roots at frequency $^{\pi/2}$.

Suboptimal filtering and nonlinear time scale transformation for the analysis of multiexponential decays

Multiexponential decays may contain time-constants differing in several orders of magnitudes. In such cases, uniform sampling results in very long records featuring a high degree of oversampling at the final part of the transient. Here, we analyze a nonlinear time scale transformation to reduce the total number of samples with minimum signal distortion, achieving an important reduction of the computational cost of subsequent analyses. We propose a time-varying filter whose length is optimized for minimum mean square error

Improved multiexponential transient spectroscopy by iterative deconvolution

The analysis of multiexponential decays is challenging because of their complex nature. When analyzing these signals, not only the parameters, but also the orders of the models, have to be estimated. We present an improved spectroscopic technique specially suited for this purpose. The proposed algorithm combines an iterative linear filter with an iterative deconvolution method. A thorough analysis of the noise effect is presented. The performance is tested with synthetic and experimental data.

Microinductive signal conditioning with resonant differential filters: high-sensitivity biodetection applications

Inductive-based devices integrated with Si technology for biodetection applications are characterized, using simple resonant differential filter configurations. This has allowed the corroboration of the viability of the proposed circuits, which are characterized by their very high simplicity, for microinductive signal conditioning in high-sensitivity sensor devices. The simulation of these simple circuits predicts sensitivities of the differential output voltage which can achieve values in the range of 0.1-1 V/nH, depending on the coil parameters. These very high-sensitivity values open the possibility for the experimental detection of extremely small inductance changes in the devices. For real microinductive devices, both series resistance and parasitic capacitive components contribute to the decrease of the differential circuit sensitivity. Nevertheless, measurements performed using micro-coils fabricated with relatively high series resistance and coupling parasitic effects have allowed detection of changes in the range of 2 nH. which are compatible with biodetection applications with estimated detection limits below the picomolarity range.

Using the HEGY Procedure When Not All Roots Are Present

Empirical studies have shown little evidence to support the presence of all unit roots present in the $^{\Delta_4}$ filter in quarterly seasonal time series. This paper analyses the performance of the Hylleberg, Engle, Granger and Yoo (1990) (HEGY) procedure when the roots under the null are not all present. We exploit the Vector of Quarters representation and cointegration relationship between the quarters when factors $(1-L),(1+L),\bigg(1+L^2\bigg),\bigg(1-L^2\bigg) y \bigg(1+L+L^2+L^3\bigg)$ are a source of nonstationarity in a process in order to obtain the distribution of tests of the HEGY procedure when the underlying processes have a root at the zero, Nyquist frequency, two complex conjugates of frequency $^{\pi/2}$ and two combinations of the previous cases. We show both theoretically and through a Monte-Carlo analysis that the t-ratios $^{t_{{\hat\pi}_1}}$ and $^{t_{{\hat\pi}_2}}$ and the F-type tests used in the HEGY procedure have the same distribution as under the null of a seasonal random walk when the root(s) is/are present, although this is not the case for the t-ratio tests associated with unit roots at frequency $^{\pi/2}$.

Potencialidad de la modelización state-space y el filtro de Kalman para el anàlisis regional : una aplicación para el índice de actividad industrial

El déficit existente a nuestro país con respecto a la disponibilidad de indicadores cuantitativos con los que llevar a término un análisis coyuntural de la actividad industrial regional ha abierto un debate centrado en el estudio de cuál es la metodología más adecuada para elaborar indicadores de estas características. Dentro de este marco, en este trabajo se presentan las principales conclusiones obtenidas en anteriores estudios (Clar, et. al., 1997a, 1997b y 1998) sobre la idoneidad de extender las metodologías que actualmente se están aplicando a las regiones españolas para elaborar indicadores de la actividad industrial mediante métodos indirectos. Estas conclusiones llevan a plantear una estrategia distinta a las que actualmente se vienen aplicando. En concreto, se propone (siguiendo a Israilevich y Kuttner, 1993) un modelo de variables latentes para estimar el indicador de la producción industrial regional. Este tipo de modelo puede especificarse en términos de un modelo statespace y estimarse mediante el filtro de Kalman. Para validar la metodología propuesta se estiman unos indicadores de acuerdo con ella para tres de las cuatro regiones españolas que disponen d¿un Índice de Producción Industrial (IPI) elaborado mediante el método directo (Andalucía, Asturias y el País Vasco) y se comparan con los IPIs publicados (oficiales). Los resultados obtenidos muestran el buen comportamiento de l¿estrategia propuesta, abriendo así una línea de trabajo con la que subsanar el déficit al que se hacía referencia anteriormente

Optical correlation by use of partial phase-only modulation with VGA liquid-crystal displays

The development of liquid-crystal panels for use in commercial equipment has been aimed at improving the pixel resolution and the display efficiency. These improvements have led to a reduction in the thickness of such devices, among other outcomes, that involves a loss in phase modulation. We propose a modification of the classical phase-only filter to permit displays in VGA liquid-crystal panels with a constant amplitude modulation and less than a 2¿(PI) phase modulation. The method was tested experimentally in an optical setup.

Application of fuzzy-rule-based postprocessing to correlation methods in pattern recognition

One of the most important problems in optical pattern recognition by correlation is the appearance of sidelobes in the correlation plane, which causes false alarms. We present a method that eliminate sidelobes of up to a given height if certain conditions are satisfied. The method can be applied to any generalized synthetic discriminant function filter and is capable of rejecting lateral peaks that are even higher than the central correlation. Satisfactory results were obtained in both computer simulations and optical implementation.

Evidence of chemical reactions in the hydroxyapatite laser ablation plume with a water atmosphere

The expansion dynamics of the ablation plume generated by KrF laser irradiation of hydroxyapatite targets in a 0.1 mbar water atmosphere has been studied by fast intensified charge coupled device imaging with the aid of optical bandpass filters. The aim of the filters is to isolate the emission of a single species, which allows separate analysis of its expansion. Images obtained without a filter revealed two emissive components in the plume, which expand at different velocities for delay times of up to 1.1 ¿s. The dynamics of the first component is similar to that of a spherical shock wave, whereas the second component, smaller than the first, expands at constant velocity. Images obtained through a 520 nm filter show that the luminous intensity distribution and evolution of emissive atomic calcium is almost identical to those of the first component of the total emission and that there is no contribution from this species to the emission from the second component of the plume. The analysis through a 780 nm filter reveals that atomic oxygen partially diffuses into the water atmosphere and that there is a contribution from this species to the emission from the second component. The last species studied here, calcium oxide, was analyzed by means of a 600 nm filter. The images revealed an intensity pattern more complex than those from the atomic species. Calcium oxide also contributes to the emission from the second component. Finally, all the experiments were repeated in a Ne atmosphere. Comparison of the images revealed chemical reactions between the first component of the plume and the water atmosphere.

Space and momentum representation analysis of Hartman's effect in wave packet transmission

The Hartman effect is analyzed in both the position and momentum representations of the problem. The importance of Wigner tunneling and deep tunneling is singled out. It is shown quantitatively how the barrier acts as a filter for low momenta (quantum speed up) as the width increases, and a detailed mechanism is proposed. Superluminal transmission is also discussed.

Benthic macroinvertebrates assemblages and macrohabitat connectivity in Mediterranean-climate streams of northern California

Abstract. Drought leads to a loss of longitudinal and lateral hydrologic connectivity, which causes direct or indirect changes in stream ecosystem properties. Changes in macrohabitat availability from a rifflepool sequence to isolated pools are among the most conspicuous consequences of connectivity loss. Macroinvertebrate assemblages were compared among 3 distinct stream macrohabitats (riffles [R], pools connected to riffles [Pc], disconnected pools [Pd]) of 19 Mediterranean-climate sites in northern California to examine the influence of loss of habitat resulting from drought disturbance. At the time of sampling, 10 sites were perennial and included R and Pc macrohabitats, whereas 9 sites were intermittent and included only Pd macrohabitats. Taxa richness was more variable in Pd, and taxa richness was significantly lower in Pd than in Pc but not R. These results suggested a decline in richness between Pc and Pd that might be associated with loss of connectivity. Lower Ephemeroptera, Plecoptera, and Trichoptera (EPT) richness relative to Odonata, Coleoptera, and Heteroptera (OCH) richness was observed for Pd than R and Pc macrohabitats. Family composition was more similar between R and Pc than between R or Pc and Pd macrohabitats. This similarity may be associated with greater connectivity between R and Pc macrohabitats. Correspondence analysis indicated that macroinvertebrate composition changed along a gradient from R to Pc and Pd that was related to a perennialintermittent gradient across sites. High variability among macroinvertebrate assemblages in Pd could have been related to variability in the duration of intermittency. In cluster analysis, macroinvertebrate assemblages were grouped by macrohabitat first and then by site, suggesting that the macrohabitat filter had a greater influence on macroinvertebrate assemblages than did local site characteristics. Few taxa were found exclusively in Pc, and this macrohabitat shared numerous taxa with R and Pd, indicating that Pc may act as a bridge between R and Pd during drought. Drought is regarded as a ramp disturbance, but our results suggest that the response of macroinvertebrate assemblages to the loss of hydrological connectivity among macrohabitats is gradual, at least in Mediterranean-climate streams where drying is gradual. However, the changes may be more dramatic in arid and semiarid streams or in Mediterranean-climate streams if drying is rapid.

Evolutionary analysis of genetic variants involved in rare diseases

Next-generation sequencing techniques such as exome sequencing can successfully detect all genetic variants in a human exome and it has been useful together with the implementation of variant filters to identify causing-disease mutations. Two filters aremainly used for the mutations identification: low allele frequency and the computational annotation of the genetic variant. Bioinformatic tools to predict the effect of a givenvariant may have errors due to the existing bias in databases and sometimes show a limited coincidence among them. Advances in functional and comparative genomics are needed in order to properly annotate these variants.The goal of this study is to: first, functionally annotate Common Variable Immunodeficiency disease (CVID) variants with the available bioinformatic methods in order to assess the reliability of these strategies. Sencondly, as the development of new methods to reduce the number of candidate genetic variants is an active and necessary field of research, we are exploring the utility of gene function information at organism level as a filter for rare disease genes identification. Recently, it has been proposed that only 10-15% of human genes are essential and therefore we would expect that severe rare diseases are mostly caused by mutations on them. Our goal is to determine whether or not these rare and severe diseases are caused by deleterious mutations in these essential genes. If this hypothesis were true, taking into account essential genes as a filter would be an interesting parameter to identify causingdisease mutations.

Susceptibilitat genètica al càncer gàstric: caracterització de les interaccions de segon ordre entre gens i variants identificades en l’estudi EPIC‐EURGAST

En aquest Treball de Final de Grau s’exposen els resultats de l’anàlisi de les dades genètiques del projecte EurGast2 "Genetic susceptibility, environmental exposure and gastric cancer risk in an European population”, estudi cas‐control niat a la cohort europea EPIC “European Prospective lnvestigation into Cancer and Nutrition”, que té per objectiu l’estudi dels factors genètics i ambientals associats amb el risc de desenvolupar càncer gàstric (CG). A partir de les dades resultants de l’estudi EurGast2, en el què es van analitzar 1.294 SNPs en 365 casos de càncer gàstric i 1.284 controls en l’anàlisi Single SNP previ, la hipòtesi de partida del present Treball de Final de Grau és que algunes variants amb un efecte marginal molt feble, però que conjuntament amb altres variants estarien associades al risc de CG, podrien no haver‐se detectat. Així doncs, l’objectiu principal del projecte és la identificació d’interaccions de segon ordre entre variants genètiques de gens candidats implicades en la carcinogènesi de càncer gàstric. L’anàlisi de les interaccions s’ha dut a terme aplicant el mètode estadístic Model‐based Multifactor Dimensionality Reduction Method (MB‐MDR), desenvolupat per Calle et al. l’any 2008 i s’han aplicat dues metodologies de filtratge per seleccionar les interaccions que s’exploraran: 1) filtratge d’interaccions amb un SNP significatiu en el Single SNP analysis i 2) filtratge d’interaccions segons la mesura Sinèrgia. Els resultats del projecte han identificat 5 interaccions de segon ordre entre SNPs associades significativament amb un major risc de desenvolupar càncer gàstric, amb p‐valor inferior a 10‐4. Les interaccions identificades corresponen a interaccions entre els gens MPO i CDH1, XRCC1 i GAS6, ADH1B i NR5A2 i IL4R i IL1RN (que s’ha validat en les dues metodologies de filtratge). Excepte CDH1, cap altre d’aquests gens s’havia associat significativament amb el CG o prioritzat en les anàlisis prèvies, el que confirma l’interès d’analitzar les interaccions genètiques de segon ordre. Aquestes poden ser un punt de partida per altres anàlisis destinades a confirmar gens putatius i a estudiar a nivell biològic i molecular els mecanismes de carcinogènesi, i orientades a la recerca de noves dianes terapèutiques i mètodes de diagnosi i pronòstic més eficients.

Multiway Array Decomposition Analysis of EEGs in Alzheimer’s Disease

Methods for the extraction of features from physiological datasets are growing needs as clinical investigations of Alzheimer’s disease (AD) in large and heterogeneous population increase. General tools allowing diagnostic regardless of recording sites, such as different hospitals, are essential and if combined to inexpensive non-invasive methods could critically improve mass screening of subjects with AD. In this study, we applied three state of the art multiway array decomposition (MAD) methods to extract features from electroencephalograms (EEGs) of AD patients obtained from multiple sites. In comparison to MAD, spectral-spatial average filter (SSFs) of control and AD subjects were used as well as a common blind source separation method, algorithm for multiple unknown signal extraction (AMUSE). We trained a feed-forward multilayer perceptron (MLP) to validate and optimize AD classification from two independent databases. Using a third EEG dataset, we demonstrated that features extracted from MAD outperformed features obtained from SSFs AMUSE in terms of root mean squared error (RMSE) and reaching up to 100% of accuracy in test condition. We propose that MAD maybe a useful tool to extract features for AD diagnosis offering great generalization across multi-site databases and opening doors to the discovery of new characterization of the disease.